The Hanjiang River, the largest tributaries of the Changjiang (Yangtze) River, is the water source area of the Middle Route
of China’s South-to-North Water Transfer Project. The chemical and strontium isotopic compositions of the river waters are
determined with the main purpose of understanding the contribution of chemical weathering processes and anthropogenic inputs
on river solutes, as well as the associated CO2 consumption in the carbonate-dominated basin. The major ion compositions of the Hanjiang River waters are characterized by
the dominance of Ca2+ and HCO3−, followed by Mg2+ and SO42−. The increase in TDS and major anions (Cl−, NO3−, and SO42−) concentrations from upstream to downstream is ascribed to both extensive influences from agriculture and domestic activities
over the Hanjiang basin. The chemical and Sr isotopic analyses indicate that three major weathering sources (dolomite, limestone,
and silicates) contribute to the total dissolved loads. The contributions of the different end-members to the dissolved load
are calculated with the mass balance approach. The calculated results show that the dissolved load is dominated by carbonates
weathering, the contribution of which accounts for about 79.4% for the Hanjiang River. The silicate weathering and anthropogenic
contributions are approximately 12.3 and 6.87%, respectively. The total TDS fluxes from chemical weathering calculated for
the water source area (the upper Hanjiang basin) and the whole Hanjiang basin are approximately 3.8 × 106 and 6.1 × 106 ton/year, respectively. The total chemical weathering (carbonate and silicate) rate for the Hanjiang basin is approximately
38.5 ton/km2/year or 18.6 mm/k year, which is higher than global mean values. The fluxes of CO2 consumption by carbonate and silicate weathering are estimated to be 56.4 × 109 and 12.9 × 109 mol/year, respectively. 相似文献
A multidimensional version of the time varying periodogram has been developed. The estimation method based on the multidimensional time-varying periodogram has been applied to a nonstationary multidimensional storm model. This work proposes that the multidimensional time varying periodogram is capable of estimating nonstationary spectral density functions in space and time.相似文献